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Particle Filtering for Quantized Sensor Information
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2005 (English)In: Proceedings of the 13th European Signal Processing Conference, 2005, 201-204 p.Conference paper, Published paper (Refereed)
Abstract [en]

The implication of quantized sensor information on filtering problems is studied. The Cramer-Rao lower bound (CRLB) is derived for estimation and filtering on quantized data. A particle filter (PF) algorithm that approximates the optimal nonlinear filter is provided, and numerical experiments show that the PF attains the CRLB, while second-order optimal Kalman filter (KF) approaches can perform quite bad.

Place, publisher, year, edition, pages
2005. 201-204 p.
Keyword [en]
Cramér-Rao lower bound, Particle filter, Kalman filter
National Category
Engineering and Technology Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-29613Local ID: 14992ISBN: 9781604238211 (print)OAI: oai:DiVA.org:liu-29613DiVA: diva2:250430
Conference
13th European Signal Processing Conference, Antalya, Turkey, September, 2005
Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2013-03-22

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Karlsson, RickardGustafsson, Fredrik

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